美国华盛顿大学生物统计专业介绍
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Takumi Saegusa (UW Biostat) Biostat PhD April 17 2013 12 / 35
Biostatistics?
hypothetical example: breastfeeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
Salary (Biostat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
18 / 35
Biostatistics?
Salary (Industry)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
Introduction to Biostatistics PhD programs
Takumi Saegusa
University of Washington Department of Biostatistics
April 17 2013
Takumi Saegusa (UW Biostat)
Biostat PhD
Ask yourself Do you have passion? Do you have patience?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
21 / 35
Apply to Grad Schools
Which Schools to Apply?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
11 / 35
Biostatistics?
HIV clinical trials
Breastfeeding was confirmed as a risk factor of the mother-to-child transmission (MTCT) in a randomized clinical trial around 2000 WHO does not recommend mixed feeding (breastfeeding + formula feeding) T : time to infection 0 = t0 < t1 < t2 < . . . < tp : observation times infection-free probability at time ti (no censoring): S (ti ) = P (infection free more than time ti ) = P (T > ti ) = P (T ≥ ti +1 ) = P (T ≥ ti +1 |T ≥ ti )P (T ≥ ti |T ≥ ti −1 ) . . . ×P (T ≥ t1 |T ≥ t0 )P (T = t0 ) # uninfected at ti +1 # uninfected at t1 ≈ × ··· # uninfected at ti # uninfected at t0
Takumi Saegusa (UW Biostat)
来自百度文库Biostat PhD
April 17 2013
8 / 35
Biostatistics?
Air Pollution Study
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
9 / 35
Biostatistics?
19 / 35
Apply to Grad Schools
APPLYING TO GRAD SCHOOLS
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
20 / 35
Apply to Grad Schools
Before Applying...
Air Pollution Study
Data are scattered over a region Data are scattered over time points (different measurements) Data are measured with errors
Takumi Saegusa (UW Biostat)
4 / 35
Biostatistics?
Sequential Clinical trial
FDA requires clinical trials for a new drug approval Sample size calculation Mean vs Median (Doesn’t matter? Really?)
Get rankings (usnews, www.phds.org, etc.) (= difficulty of getting in) Is funding available to all students (including master’s students)? Proportions of PhD students successfully completing the program Average years of completion. Careers after graduate schools Possible to change from a master’s program to a PhD program? Male vs. Female, American vs Intl’ Students, Class size, etc. culture, weather, etc. Visit campus if you can (ask graduate programs)
t2 60 5 15 60/(100-20) .6
t3 40 5 15 40/(80-20) .4
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
15 / 35
Biostatistics?
Career as a Statistician
0 100 0 0 NA 1
t1 90 10 0 90/100 1 × .9
t2 70 10 10 70/(100-10) .9 × 7/9 = .7
t3 50 10 10 50/(90-10-10) .7 × 5/7 = .5
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Balanced Development: Math + Science + YOU Methodological research
Theory
Methods
Applications
Biostatistics
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
0 100 0 0 NA 1.0
t1 80 0 20 1.0 1.0
t2 60 0 20 1.0 1.0
t3 40 0 20 1.0 1.0
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
14 / 35
Biostat PhD
April 17 2013
23 / 35
Apply to Grad Schools
What does an admission committee want to know about you?
Biostatistics?
hypothetical example: mixed feeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
0 100 0 0 NA 1.0
t1 80 5 15 80/100 .8
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
22 / 35
Apply to Grad Schools
What does an admission committee want to know about you?
Takumi Saegusa (UW Biostat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
5 / 35
Biostatistics?
Sequential Clinical trial
Should we stop early if a new drug is “clearly” beneficial or harmful?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
7 / 35
Biostatistics?
Network estimation
Estimate covariance matrix in high dimension Regularization (penalized MLE)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
6 / 35
Biostatistics?
Network estimation
Central Dogma: Gene → RNA → Protein Abundance of thousands of mRNAs is measured by microarray at once
Biostat PhD
April 17 2013
13 / 35
Biostatistics?
hypothetical example: formula feeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
16 / 35
Biostatistics?
Salary (Stat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
17 / 35
Biostatistics?
April 17 2013
1 / 35
Outline
What is Biostatistics? Applying to Graduate Schools Survival Guide
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
2 / 35
Biostatistics?
WHAT IS BIOSTATISTICS?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
3 / 35
Biostatistics?
Statistics = Theory + Methods + Applications
Website of the American Statistical Association (http://www.amstat.org/careers) Government survey Industry (drug development, quality control, market research) Academia (statistical research, scientific research ) etc.
Biostat PhD
April 17 2013
10 / 35
Biostatistics?
HIV clinical trials
censoring: no information after time T = information that she live more than T death: censoring or outcome?
Biostatistics?
hypothetical example: breastfeeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
Salary (Biostat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
18 / 35
Biostatistics?
Salary (Industry)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
Introduction to Biostatistics PhD programs
Takumi Saegusa
University of Washington Department of Biostatistics
April 17 2013
Takumi Saegusa (UW Biostat)
Biostat PhD
Ask yourself Do you have passion? Do you have patience?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
21 / 35
Apply to Grad Schools
Which Schools to Apply?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
11 / 35
Biostatistics?
HIV clinical trials
Breastfeeding was confirmed as a risk factor of the mother-to-child transmission (MTCT) in a randomized clinical trial around 2000 WHO does not recommend mixed feeding (breastfeeding + formula feeding) T : time to infection 0 = t0 < t1 < t2 < . . . < tp : observation times infection-free probability at time ti (no censoring): S (ti ) = P (infection free more than time ti ) = P (T > ti ) = P (T ≥ ti +1 ) = P (T ≥ ti +1 |T ≥ ti )P (T ≥ ti |T ≥ ti −1 ) . . . ×P (T ≥ t1 |T ≥ t0 )P (T = t0 ) # uninfected at ti +1 # uninfected at t1 ≈ × ··· # uninfected at ti # uninfected at t0
Takumi Saegusa (UW Biostat)
来自百度文库Biostat PhD
April 17 2013
8 / 35
Biostatistics?
Air Pollution Study
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
9 / 35
Biostatistics?
19 / 35
Apply to Grad Schools
APPLYING TO GRAD SCHOOLS
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
20 / 35
Apply to Grad Schools
Before Applying...
Air Pollution Study
Data are scattered over a region Data are scattered over time points (different measurements) Data are measured with errors
Takumi Saegusa (UW Biostat)
4 / 35
Biostatistics?
Sequential Clinical trial
FDA requires clinical trials for a new drug approval Sample size calculation Mean vs Median (Doesn’t matter? Really?)
Get rankings (usnews, www.phds.org, etc.) (= difficulty of getting in) Is funding available to all students (including master’s students)? Proportions of PhD students successfully completing the program Average years of completion. Careers after graduate schools Possible to change from a master’s program to a PhD program? Male vs. Female, American vs Intl’ Students, Class size, etc. culture, weather, etc. Visit campus if you can (ask graduate programs)
t2 60 5 15 60/(100-20) .6
t3 40 5 15 40/(80-20) .4
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
15 / 35
Biostatistics?
Career as a Statistician
0 100 0 0 NA 1
t1 90 10 0 90/100 1 × .9
t2 70 10 10 70/(100-10) .9 × 7/9 = .7
t3 50 10 10 50/(90-10-10) .7 × 5/7 = .5
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Balanced Development: Math + Science + YOU Methodological research
Theory
Methods
Applications
Biostatistics
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
0 100 0 0 NA 1.0
t1 80 0 20 1.0 1.0
t2 60 0 20 1.0 1.0
t3 40 0 20 1.0 1.0
··· ··· ··· ··· ··· ···
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
14 / 35
Biostat PhD
April 17 2013
23 / 35
Apply to Grad Schools
What does an admission committee want to know about you?
Biostatistics?
hypothetical example: mixed feeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
0 100 0 0 NA 1.0
t1 80 5 15 80/100 .8
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
22 / 35
Apply to Grad Schools
What does an admission committee want to know about you?
Takumi Saegusa (UW Biostat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
5 / 35
Biostatistics?
Sequential Clinical trial
Should we stop early if a new drug is “clearly” beneficial or harmful?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
7 / 35
Biostatistics?
Network estimation
Estimate covariance matrix in high dimension Regularization (penalized MLE)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
6 / 35
Biostatistics?
Network estimation
Central Dogma: Gene → RNA → Protein Abundance of thousands of mRNAs is measured by microarray at once
Biostat PhD
April 17 2013
13 / 35
Biostatistics?
hypothetical example: formula feeding
time # uninfected # infected # missing before ti P (T ≥ ti |T ≥ ti −1 ) S (t )
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
16 / 35
Biostatistics?
Salary (Stat)
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
17 / 35
Biostatistics?
April 17 2013
1 / 35
Outline
What is Biostatistics? Applying to Graduate Schools Survival Guide
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
2 / 35
Biostatistics?
WHAT IS BIOSTATISTICS?
Takumi Saegusa (UW Biostat)
Biostat PhD
April 17 2013
3 / 35
Biostatistics?
Statistics = Theory + Methods + Applications
Website of the American Statistical Association (http://www.amstat.org/careers) Government survey Industry (drug development, quality control, market research) Academia (statistical research, scientific research ) etc.
Biostat PhD
April 17 2013
10 / 35
Biostatistics?
HIV clinical trials
censoring: no information after time T = information that she live more than T death: censoring or outcome?